{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120391"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120391","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A structured matrix factorization method for computational modeling of hierarchical polarization in social interactions","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","abstract_has_math":false,"creators":["Sun, Dachun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Abdelzaher, Tarek"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Polarization","Belief Estimation","Hierarchical","Matrix Factorization","Unsupervised"],"languages":["en","eng"],"rights":["Copyright 2023 Dachun Sun"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120391","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Abdelzaher, Tarek"]},{"key":"dc:creator","label":"Author","values":["Sun, Dachun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-04-20"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Polarization","Belief Estimation","Hierarchical","Matrix Factorization","Unsupervised"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Dachun Sun"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120391"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","The student, Dachun Sun, accepted the attached license on 2023-04-19 at 18:31.","The student, Dachun Sun, submitted this Thesis for approval on 2023-04-19 at 18:37.","This Thesis was approved for publication on 2023-04-20 at 14:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19052 on 2023-09-01 at 17:13:45","Many works on social interaction polarization detection focus heavily on flat classification of stances and beliefs. We extend them in this work in two important aspects: (i) detects both points of agreement and disagreement between groups, and (ii) divides them hierarchically to represent nested patterns of agreement and disagreement given a structural guide. For example, two opposing parties might disagree on core issues. Moreover, a disagreement might occur on further details within a party, despite agreement on the fundamentals. We call such scenarios hierarchically polarization. An unsupervised Non-negative Matrix Factorization (NMF) algorithm is described for the computational modeling of hierarchical polarization in social interactions. The algorithm is enhanced with a language model and a proof of orthogonality of factorized components. We evaluate it on both synthetic and real-world datasets, demonstrating the ability to decompose overlapping beliefs hierarchically. In the case where polarization is flat, we compare it to the prior art and show that it outperforms state-of-the-art approaches for polarization detection and stance separation. An ablation study further illustrates the value of individual components, including new enhancements."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A structured matrix factorization method for computational modeling of hierarchical polarization in social interactions"]}]}],"canonical_facts":{"dc:contributor":["Abdelzaher, Tarek"],"dc:creator":["Sun, Dachun"],"dc:date":["2023-05","2023-04-20"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","The student, Dachun Sun, accepted the attached license on 2023-04-19 at 18:31.","The student, Dachun Sun, submitted this Thesis for approval on 2023-04-19 at 18:37.","This Thesis was approved for publication on 2023-04-20 at 14:53.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19052 on 2023-09-01 at 17:13:45","Many works on social interaction polarization detection focus heavily on flat classification of stances and beliefs. We extend them in this work in two important aspects: (i) detects both points of agreement and disagreement between groups, and (ii) divides them hierarchically to represent nested patterns of agreement and disagreement given a structural guide. For example, two opposing parties might disagree on core issues. Moreover, a disagreement might occur on further details within a party, despite agreement on the fundamentals. We call such scenarios hierarchically polarization. An unsupervised Non-negative Matrix Factorization (NMF) algorithm is described for the computational modeling of hierarchical polarization in social interactions. The algorithm is enhanced with a language model and a proof of orthogonality of factorized components. We evaluate it on both synthetic and real-world datasets, demonstrating the ability to decompose overlapping beliefs hierarchically. In the case where polarization is flat, we compare it to the prior art and show that it outperforms state-of-the-art approaches for polarization detection and stance separation. An ablation study further illustrates the value of individual components, including new enhancements."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120391"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Dachun Sun"],"dc:subject":["Polarization","Belief Estimation","Hierarchical","Matrix Factorization","Unsupervised"],"dc:title":["A structured matrix factorization method for computational modeling of hierarchical polarization in social interactions"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}